Data Exfiltration Prevention
Advanced data loss prevention for AI systems — context window controls, output classification, covert channel detection, and the architectural patterns that prevent AI agents from becoming data exfiltration tools.
9 Lessons · ~0.3 Hours · 3 Modules
Instructor: DRILL — Academy Director
Module 1: AI-Specific Exfiltration Vectors
How AI systems create novel data exfiltration channels that traditional DLP does not detect — and the classification framework for understanding each vector.
- The Model as Exfiltration Channel (4 min read)
- Covert Exfiltration Channels (3 min read)
- Data Classification for AI Context (3 min read)
Module 2: Prevention Architecture
Architectural patterns that prevent exfiltration by design — input-side controls, output-side controls, and the separation principles that contain exposure.
- Context Minimization (3 min read)
- Output Classification Pipeline (4 min read)
- Separation of Data and Action (3 min read)
Module 3: Detection and Response
Detecting exfiltration in progress, responding to confirmed data loss, and building the forensic capability that determines what was taken.
- Exfiltration Detection Patterns (3 min read)
- Data Loss Response (3 min read)
- Building Exfiltration Resilience (3 min read)